
    
Ng%                     Z   d dl Z d dlmZmZmZmZmZ d dlZd dl	Z	d dl	m
Z
mZ d dlmZ d dlmZmZmZ d dlmZmZmZmZmZ d dlmZ d dlmZmZ  ed	  e            D             d
           Z ed  e            D             d           Zdee ee!eee!e df         df         f         f         dee ef         fdZ"	 ddedee          dee          dee ef         deee ej#        f                  dee ef         fdZ$ G d de j%                  Z&e'dk    r e j(                     dS dS )    N)DictListOptionalTupleUnion)TensorProto	TypeProto)ValidationError)OpSchemaget_all_schemas_with_history
get_schema)
make_graph	make_nodemake_opsetidmake_tensor_type_protomake_tensor_value_info
from_array)InferenceErrorinfer_node_outputsc              #   F   K   | ]}|j         d k    |j        dk    |V  dS )Add Nnamedomain.0ss     ]/var/www/html/ai-engine/env/lib/python3.11/site-packages/onnx/test/inference_function_test.py	<genexpr>r!      s3      UU1!&E//ahRTnnQnnnnUU    c                     | j         S Nsince_versionr   s    r    <lambda>r(          !/ r"   )keyc              #   F   K   | ]}|j         d k    |j        dk    |V  dS )Reshaper   Nr   r   s     r    r!   r!      sB        6Y18r>> 	
#1>>> r"   c                     | j         S r$   r%   r'   s    r    r(   r(   "   r)   r"   tensor_types.returnc                 >    d |                                  D             S )Nc                 (    i | ]\  }}|t          | S  )r   )r   r*   values      r    
<dictcomp>z$_to_tensor_types.<locals>.<dictcomp>)   s$    WWWJCC'/WWWr"   )items)r.   s    r    _to_tensor_typesr6   &   s%     XW,BTBTBVBVWWWWr"   schemainput_namesoutput_namesinput_types
input_datac           	          |i }t          | t          | j        ||| j                  |d |                                D                       S )N)r   c                 4    i | ]\  }}|t          |          S r2   r   )r   r*   arrs      r    r4   z_run_case.<locals>.<dictcomp>9   s$    AAA(#sjooAAAr"   )r   r   r   r   r5   )r7   r8   r9   r:   r;   s        r    	_run_caser?   ,   s\     
&+{LOOOAAj.>.>.@.@AAA	  r"   c                   >    e Zd Zd	dZd	dZd	dZd	dZd	dZd	dZdS )
TestInferenceFunctionCallr/   Nc           	      F   t           j        dft           j        dfddt           j        dfift           j        dft           j        dfddt           j        dfift           j        dft           j        dfddt           j        dfift           j        dft           j        dfddt           j        dfift           j        d	ft           j        d
fddt           j        dfifg}|D ]?\  }}t          t          ddgdgt          |                    t          |          k    sJ @d S )Nr2   ABC)N   )rG   )   rG   )nm)rH   rI   rJ   )xrG   )yrG   rD   rE   )r   FLOATDOUBLEr?   
ADD_SCHEMAr6   )selfcasesinsoutss       r    test_add_inferencez,TestInferenceFunctionCall.test_add_inference>   s~    #("-[5F4KLL{("-. &+Y7%+T2  {()45 &+Y7%+V4  {()45 &,j9%,m<  {)=9: &+X6%+X6  {()455!
D  	m 	mICZ#scU<LS<Q<QRRVfgkVlVllllll	m 	mr"   c                 Z   |                      t                    5  t          t          dgdgt	          dt
          j        dfi                     d d d            n# 1 swxY w Y   |                      t                    5  t          t          ddgdgt	          t
          j        dfdd                     d d d            n# 1 swxY w Y   |                      t                    5  t          t          ddgdgt	          t
          j        dft
          j        dfd                     d d d            n# 1 swxY w Y   |                      t                    5  t          t          ddgdgt	          dt
          j        dfi                     d d d            d S # 1 swxY w Y   d S )NrD   rF         rE   )rG   rV   rC   )rG   rX   )	assertRaisesr
   r?   rO   r6   r   rM   r   KeyErrorrP   s    r     test_add_inference_raises_errorsz:TestInferenceFunctionCall.test_add_inference_raises_errorsd   s   // 	 	 #(96'B!CDD	  	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 // 	 	c
 (96'B!U!UVV	  	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 ~.. 	 	c
 )/8)/8  	
 
 
	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 x(( 	 	c
 #(96'B!CDD	  	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	sH   5AA #A 7CCC)AD88D<?D<6F  F$'F$c                    t          t          ddgdgt          t          j        dft          j        dfd          dt          j        g dt          j                  i          t          dt          j        dfi          k    sJ d S )	NrK   trL   )   rX   )rW   )rK   r^   )rG   rG   r_   )dtype)	r?   RESHAPE_SCHEMAr6   r   rM   INT64nparrayint64r[   s    r    test_reshape_inferencez0TestInferenceFunctionCall.test_reshape_inference   s    #JE%+V4%+T2   "(999BH5556
 
 s[%6	$BCDDE E E E E Er"   c           
         d}d}d}t          dt          j        d           t          dt          j        d           t          dt          j        d           g}t          dt          j        d           t          dt          j        ||f          g}t	          t          d	dgdg          t          d
ddgdg          gd||          }t          t          dd          t          dg dddgd|          t          t          j        |fft          j        ||fft          j        |ffd          t          dd          gd          t          t          j        |fft          j        ||ffd          k    sJ d S )NsequencerG   rW   loop_state_ininputouterloop_state_outoutputIdentityr   subgraphScan	   )loop_state_orig
scan_input
scan_outerloop_state_finalscan_outputrH   )num_scan_inputsbodyr   rX   )opset_imports
ir_version)ru   rv   )
r   r   	UNDEFINEDrM   r   r   r   r   r6   r   )rP   seq_len
input_sizeloop_state_sizeinput_value_infosoutput_value_infosro   s          r    !test_scan_inference_with_subgraphz;TestInferenceFunctionCall.test_scan_inference_with_subgraph   s   
 #?K4I4PP"7K,A4HH"7K,A4HH
 ##3[5JDQQ"8[->*@UVV

 *&7:J9KLL%'7!3hZ@@ 
 
 "vq!!???#]3 !   (3(9O;M'N#.#4w
6K"L#.#4zm"D   (A../%
 
 
& %0%68J$K + 1GZ3HI 
 
'
 
 
 
 
 
r"   c                 F   d}t           j                            |          }t           j                            |d           |                     t           j        j                  5  t           j                            |d           d d d            d S # 1 swxY w Y   d S )Na  
        <
            ir_version: 8,
            opset_import: ["" : 18, "onnxscript.atenlib" : 1],
            producer_name: "pytorch",
            producer_version: "2.1.0"
        >
        torch_jit (float input_0) => (float reault, int64 index)
        {
            reault, index = onnxscript.atenlib.aten_min_dim <dim = 0, keepdim = 1> (input_0)
        }
        <
            domain: "onnxscript.atenlib",
            opset_import: ["" : 18]
        >
        aten_min_dim <dim>(self) => (result_7, indices_6)
        {
            tmp = Shape (self)
            tmp_0 = Size (tmp)
            tmp_1 = Constant <value = int64 tmp_1 {0}> ()
            tmp_1_cast = CastLike (tmp_1, tmp_0)
            tmp_2 = Equal (tmp_0, tmp_1_cast)
            cond = Not (tmp_2)
            indices_6, result_7 = If (cond) <
                then_branch = thenGraph_4 () => ( indices,  result) {
                    dim = Constant <value_int: int = @dim> ()
                    tmp_3 = Constant <value_ints = [-1]> ()
                    dims = Reshape (dim, tmp_3)
                    result = ReduceMin <keepdims: int = @keepdim> (self, dims)
                    indices = ArgMin <axis: int = @dim, keepdims: int = @keepdim> (self)
                }, else_branch = elseGraph_4 () => ( indices_4,  result_5) {
                    indices_4 = Constant <value_int = 0> ()
                    result_5 = Identity (self)
                }
            >
        }
        Fstrict_modeT)onnxparserparse_modelshape_inferenceinfer_shapesrY   r   rP   model_scriptmodels      r    test_inference_with_conflowz5TestInferenceFunctionCall.test_inference_with_conflow   s    $J ''55))%U)CCCt3BCC 	G 	G --e-FFF	G 	G 	G 	G 	G 	G 	G 	G 	G 	G 	G 	G 	G 	G 	G 	G 	G 	Gs   '"BBBc                     d}t           j                            |          }t           j                            |d           d S )Na  
        <
            ir_version: 8,
            opset_import: ["" : 18, "custom" : 1],
            producer_name: "",
            producer_version: "1.0"
        >
        MeanVarianceNormalization (float[N] x) => (float[M] y)
        {
            y = custom.custom_mvn <axes = [0]> (x)
        }
        <
            domain: "custom",
            opset_import: ["" : 18]
        >
        custom_mvn <axes>(X) => (Y)
        {
          Exponent = Constant <value = float {2.0}>()
          Epsilon = Constant <value = float {1e-9}>()
          axes = Constant <value_ints: ints = @axes>()
          X_RM = ReduceMean (X, axes)
          EX_squared = Pow (X_RM, Exponent)
          X_squared = Pow (X, Exponent)
          E_Xsquared = ReduceMean (X_squared, axes)
          Variance = Sub (E_Xsquared, EX_squared)
          STD = Sqrt (Variance)
          X_variance = Sub (X, X_RM)
          Processed_STD = Add (STD, Epsilon)
          Y = Div (X_variance, Processed_STD)
        }
        Tr   )r   r   r   r   r   r   s      r    test_inference_with_attributez7TestInferenceFunctionCall.test_inference_with_attribute   sB    > ''55))%T)BBBBBr"   )r/   N)	__name__
__module____qualname__rT   r\   rf   r   r   r   r2   r"   r    rA   rA   =   s        $m $m $m $mL! ! ! !FE E E E1
 1
 1
 1
f)G )G )G )GV"C "C "C "C "C "Cr"   rA   __main__r$   ))unittesttypingr   r   r   r   r   numpyrc   r   r   r	   onnx.checkerr
   	onnx.defsr   r   r   onnx.helperr   r   r   r   r   onnx.numpy_helperr   onnx.shape_inferencer   r   maxrO   ra   strintr6   ndarrayr?   TestCaserA   r   mainr2   r"   r    <module>r      s  
  5 5 5 5 5 5 5 5 5 5 5 5 5 5      ' ' ' ' ' ' ' ' ( ( ( ( ( ( H H H H H H H H H H              ) ( ( ( ( ( C C C C C C C CSUU,,..UUU!!  
  --//  
 	"!  XsE#uU3T>-BC-G'H"HIIJX	#y.X X X X 37 c s) c9n%	
 c2:o./ 
#y.   "XC XC XC XC XC 1 XC XC XCv zHMOOOOO r"   